Rowe Alexander K, Kachur S Patrick, Yoon Steven S, Lynch Matthew, Slutsker Laurence, Steketee Richard W
Malaria Branch, Division of Parasitic Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Malar J. 2009 Sep 3;8:209. doi: 10.1186/1475-2875-8-209.
The global health community is interested in the health impact of the billions of dollars invested to fight malaria in Africa. A recent publication used trends in malaria cases and deaths based on health facility records to evaluate the impact of malaria control efforts in Rwanda and Ethiopia. Although the authors demonstrate the use of facility-based data to estimate the impact of malaria control efforts, they also illustrate several pitfalls of such analyses that should be avoided, minimized, or actively acknowledged. A critique of this analysis is presented because many country programmes and donors are interested in evaluating programmatic impact with facility-based data. Key concerns related to: 1) clarifying the objective of the analysis; 2) data validity; 3) data representativeness; 4) the exploration of trends in factors that could influence malaria rates and thus confound the relationship between intervention scale-up and the observed changes in malaria outcomes; 5) the analytic approaches, including small numbers of patient outcomes, selective reporting of results, and choice of statistical and modeling methods; and 6) internal inconsistency on the strength and interpretation of the data. In conclusion, evaluations of malaria burden reduction using facility-based data could be very helpful, but those data should be collected, analysed, and interpreted with care, transparency, and a full recognition of their limitations.
全球卫生界关注在非洲投入数十亿美元抗击疟疾所产生的健康影响。最近一份出版物利用基于医疗机构记录的疟疾病例和死亡趋势,评估了卢旺达和埃塞俄比亚疟疾防控工作的影响。尽管作者展示了利用基于机构的数据来估计疟疾防控工作的影响,但他们也说明了此类分析中应避免、尽量减少或积极承认的几个陷阱。本文对该分析进行了批评,因为许多国家项目和捐助方都有兴趣利用基于机构的数据来评估项目影响。主要问题涉及:1)明确分析目标;2)数据有效性;3)数据代表性;4)探索可能影响疟疾发病率从而混淆干预扩大规模与观察到的疟疾结果变化之间关系的因素趋势;5)分析方法,包括少量患者结果、结果的选择性报告以及统计和建模方法的选择;6)数据强度和解释方面的内部不一致性。总之,利用基于机构的数据评估疟疾负担减轻情况可能非常有帮助,但这些数据的收集、分析和解释应谨慎、透明,并充分认识到其局限性。